This clinical decision support tool helps medical providers predict risk of 60-, 90-, and 180-day mortality among cancer patients, including breast, lung, ovarian, kidney, and other cancer types

This machine learning algorithm is the digital manifestation of the research paper, An Actionable Tool for Mortality Predictions in Cancer Patients by Dimitris Bertsimas, Jack Dunn, Colin Pawlowski, John Silberholz, Alexander Weinstein, Ying Daisy Zhuo, Eddy Chen, and Aymen Elfiky, that appeared JCO Clinical Cancer Informatics in June, 2018.